Prologis Shares Dip 1.38% Amid $360M Trading Volume Surge, Ranking 291st in Market Activity

On September 24, 2025, Prologis (PLD) saw a 1.38% decline in share price despite a 35.64% surge in trading volume to $360 million, ranking 291st in market activity. The logistics real estate leader remains positioned for long-term growth amid evolving market dynamics.

Prologis continues to capitalize on the logistics sector's resilience, with its 1.3 billion-square-foot portfolio serving 6,500 clients including Amazon, Walmart, and UPS. The company has demonstrated robust dividend growth, increasing payouts by 90% since 2019, outpacing broader REIT averages. Its strategic expansion into high-margin digital infrastructure further strengthens its outlook, with a $25 billion data center initiative launched in 2024 to meet AI-driven demand. Prologis has secured 3.6 gigawatts of power capacity for data center projects, aligning with projected $7 trillion in global AI infrastructure investments by 2030.

Recent operational updates highlight sustained demand momentum. A July 16 report noted "warehouse demand piling up" as tariff concerns ease, while Q2 earnings prompted a full-year 2025 outlook upgrade. The company's diversified tenant base—top 10 clients account for just 14% of total assets—reduces sector-specific risk. Its 3.5% dividend yield remains attractive compared to the S&P 500 average of 1.2%, though investors may watch for refinancing opportunities as interest rates evolve.

To run this back-test accurately I need to clarify (and, if necessary, simplify) a few practical details so the analysis fits within the capabilities of our current back-testing engine:

1. Universe definition • Should the daily “top 500 by dollar trading volume” be drawn from a specific universe such as: – All U.S. common stocks listed on NYSE / NASDAQ / AMEX, or – A predefined index membership list (e.g., Russell 3000, S&P 500), or – Another custom universe? 2. Weighting and rebalancing details • Equal-weight each of the 500 names each day? • Rebalance every trading day (i.e., sell yesterday’s basket at today’s open/close and buy today’s new basket at the same price point)? • Any transaction-cost assumption to include?

3. Practical limitations Our current toolset can back-test rules on a single ticker or evaluate event lists, but it does not natively handle a daily-changing 500-stock portfolio. A common workaround is to: • Define an ETF or index that approximates the desired exposure (for example, use an ETF whose constituents are high-volume stocks), or • Treat “entry signals” on an index proxy (e.g., SPY) as if buying the whole basket. If you need the true 500-stock daily rotation, we would have to export data and run a custom script outside this interface.

Please advise which approach you’d like to proceed with, or let me know if an approximate single-ticker proxy is acceptable.